EP0365878B1 - Image processing method - Google Patents

Image processing method Download PDF

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Publication number
EP0365878B1
EP0365878B1 EP89118325A EP89118325A EP0365878B1 EP 0365878 B1 EP0365878 B1 EP 0365878B1 EP 89118325 A EP89118325 A EP 89118325A EP 89118325 A EP89118325 A EP 89118325A EP 0365878 B1 EP0365878 B1 EP 0365878B1
Authority
EP
European Patent Office
Prior art keywords
image
data
processing method
shifted
image processing
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Expired - Lifetime
Application number
EP89118325A
Other languages
German (de)
English (en)
French (fr)
Other versions
EP0365878A3 (en
EP0365878A2 (en
Inventor
Ryohei Kumagai
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Yozan Inc
Sharp Corp
Original Assignee
Yozan Inc
Ezel Inc
Sharp Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Yozan Inc, Ezel Inc, Sharp Corp filed Critical Yozan Inc
Publication of EP0365878A2 publication Critical patent/EP0365878A2/en
Publication of EP0365878A3 publication Critical patent/EP0365878A3/en
Application granted granted Critical
Publication of EP0365878B1 publication Critical patent/EP0365878B1/en
Anticipated expiration legal-status Critical
Expired - Lifetime legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/40—Analysis of texture
    • G06T7/41—Analysis of texture based on statistical description of texture
    • G06T7/45—Analysis of texture based on statistical description of texture using co-occurrence matrix computation

Definitions

  • the present invention relates to an image processing method for generating a density cooccurrence matrix of an original image.
  • the density cooccurrence matrix is an important characteristic for texture analysis. By conventional methods, it takes a long time to generate such a density cooccurrence matrix.
  • a density cooccurrence matrix is a two dimensional expression of a relationship between the density of each pixel and other pixels.
  • the inventor supposes that by conventional methods a shifted image shifted by a predetermined distance is generated from the original image, and then corresponding pixels of both images are compared with each other. For this processing, a lot of process time is necessary when processed by a software, and a plurality of scanning at least equal to the number of graduation levels is necessary. When one time scanning is performed in video rate, it takes about one second for processing an image of 16 level graduation.
  • EPC From EP-A2-O 340 549 which forms a part of the state of the art within the meaning of Article 54 (3) EPC to the present invention an image processing method for generating an cooccurrence matrix in a very fast manner is known.
  • an original image is stored in a first memory and the shifted version of that original image is stored in a second memory.
  • the image density data stored in the second memory is successively read out and applied to a counter portion as address data. Simultaneously the corresponding data of the first memory is read out and applied to a comparator means.
  • the applied density data from the first memory is compared with a predetermined density value and in case of coincidence between the predetermined value and the currently applied density value a count signal is transmitted from the comparator means to the data input of the counter portion increasing the counter value stored under the currently selected address of the counter portion.
  • the predetermined value inputted to the comparator means is changed in order to generate by a next scanning a further row (column) of the cooccurrence matrix.
  • Fig. 1 shows an image processing system useful for one embodiment of the present invention.
  • the image processing system comprises a frame memory 1 of plurality of planes and a computational portion 3 connected through a local bus 2 to the frame memory 1.
  • a data output of the register 4 is connected to a light computational portion 5.
  • An output of the portion 5 is inputted to an data input DI of the register 4.
  • An output of the computational portion 3 is inputted to an address input A of the register 4 for designating an address of the register 4 according to the computational result of the computational portion 3.
  • the light computational portion 5 has a performance of increasing by "1" the data from a data output DO of the register 4.
  • the increased data is inputted to the data input DI of the register 4 again.
  • the register stores the number of outputting times from the computational portion 3 for each value of the computational result.
  • a shifted image (Fig. 2) by a predetermined distance (dx, dy) from an original image (Fig. 3) is generated first, for generating a density cooccurrence matrix.
  • the original image is passed through the computational portion 3 without computation, with shifting the reading timing and writing timing of the frame memory.
  • the writing timing is advanced by dx pixels to the reading timing in the scan line direction
  • an image shifted by dx in the x-direction is generated.
  • a shifted image in the y-direction is generated similarly to the above.
  • Fig. 3 shows an image shifted by a distance of (dx, dy) form the original image in Fig. 2.
  • each pixel has a data of density with a data length of 4 bits.
  • the data length of each pixel in the frame memory is 8 bits, the lower 4 bits are valid as shown in Fig. 4.
  • the invalid data of upper 4 bits can be refreshed to "0" by initializing the frame memory before storing the quantized image.
  • each data of the original image or the shifted image is shifted leftward by a length is bits equal to or more than the length is bits of the bit string of pixel data.
  • the data of bit shifting is shown in Fig. 6, which consists of upper valid 4 bits and lower "0" bit string.
  • the bit shifting is performed by the computational portion 3 which has a performance of bit shifting or a performance of multiplication by a multiplier of 2 n .
  • the data of the original image is shifted by 4 bit as shown in Fig. 6.
  • Data length of each data of shifted image by 4 bits is equal to the length of the data of the original image.
  • the data of the shifted image includes valid data of lower 4 bits, the upper 4 bits of which are "0". Since the lower 4 bits of the data of the original image are automatically changed to "0" by bit shifting and the original upper 4 bits are changed to the original lower 4 bits on the bit shifting, the original upper 4 bits may be any data. However, as for the data in Fig. 5, the upper 4 bits of the data in Fig. 5 are necessary to be "0".
  • the images of Figs 5 and 6 are parallelly inputted to the computational portion 3 which calculates addition or OR logic of data of corresponding pixels of both images.
  • the calculation result shown in Fig. 7, is inputted to the address input A of the register 4.
  • the register 4 is initialized before the processing. Data stored in each address of the register 4 finally becomes the outputting times of each value of the calculation result of the computational portion 3.
  • the upper 4 bits of the data in Fig. 7 is defined as H1, lower 4 bits as H2, and the data storaged in each address of the register as Cij.
  • the register stores a density cooccurrence matrix as shown below.
  • the computational portion 3 performs 4 bits bit shifting.
  • bit shifting When there is a limit of bit shifting, for example the multiplier has a data length less than 5 bits and therefor 4 bits bit shifting is impossible, bit shifting within the limit is performed simultaneously with the coordinate shifting by the distance.
  • Fig. 8 shows data which is shifted by one bit to the left from the data of Fig. 4.
  • the data in Fig. 8 is shifted by 3 bits simultaneously with the adding-or OR-processing.
  • the above embodiment needs 2 scannings.
  • the density cooccurrence matrix is generated by 2 scannings; one scanning for coordinate shifting and one scanning for bit shifting or other combinations. This scanning time is much smaller as with conventional methods which need scanning times of (1+m), where m is graduation levels. Therefore, the processing time is 1/m of the time needed with conventional methods.

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  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Computing Systems (AREA)
  • Mathematical Physics (AREA)
  • Probability & Statistics with Applications (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • General Physics & Mathematics (AREA)
  • Image Processing (AREA)
  • Image Analysis (AREA)
EP89118325A 1988-10-25 1989-10-03 Image processing method Expired - Lifetime EP0365878B1 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP63268908A JP2840706B2 (ja) 1988-10-25 1988-10-25 画像処理方法
JP268908/88 1988-10-25

Publications (3)

Publication Number Publication Date
EP0365878A2 EP0365878A2 (en) 1990-05-02
EP0365878A3 EP0365878A3 (en) 1991-03-20
EP0365878B1 true EP0365878B1 (en) 1995-06-14

Family

ID=17464940

Family Applications (1)

Application Number Title Priority Date Filing Date
EP89118325A Expired - Lifetime EP0365878B1 (en) 1988-10-25 1989-10-03 Image processing method

Country Status (4)

Country Link
US (1) US5103487A (ja)
EP (1) EP0365878B1 (ja)
JP (1) JP2840706B2 (ja)
DE (1) DE68923052T2 (ja)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH0795345B2 (ja) * 1988-04-21 1995-10-11 株式会社イーゼル 画像処理方法
US20060266907A1 (en) * 2005-05-31 2006-11-30 Hinden Edwin R Water-wet bar soap preserver
DE112018002572T5 (de) * 2017-05-19 2020-06-04 Movidius Ltd. Verfahren, systeme und vorrichtungen zur optimierung der pipeline-ausführung

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0110353B2 (en) * 1982-11-30 1990-03-21 Kabushiki Kaisha Toshiba Picture signal processing system suitable for displaying continuous tone pictures
US4665551A (en) * 1983-12-08 1987-05-12 Machine Vision International Corporation Apparatus and method for implementing transformations in digital image processing
JPH077441B2 (ja) * 1985-11-07 1995-01-30 富士通株式会社 濃度ヒストグラム検出装置
JPH0795345B2 (ja) * 1988-04-21 1995-10-11 株式会社イーゼル 画像処理方法

Also Published As

Publication number Publication date
EP0365878A3 (en) 1991-03-20
DE68923052T2 (de) 1995-10-19
JPH02114387A (ja) 1990-04-26
US5103487A (en) 1992-04-07
EP0365878A2 (en) 1990-05-02
JP2840706B2 (ja) 1998-12-24
DE68923052D1 (de) 1995-07-20

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